42 citations · 57 across the 2 of their papers we have counts for
8 papers
Statistical bounds for entropic optimal transport: sample complexity and the central limit theorem
Gonzalo Mena, Jonathan Weed
We prove several fundamental statistical bounds for entropic OT with the squared Euclidean cost between subgaussian probability measures in arbitrary dimension. First, through a ne…
Approximating the Quadratic Transportation Metric in Near-Linear Time
Jason Altschuler, Francis Bach, Alessandro Rudi +1
Computing the quadratic transportation metric (also called the -Wasserstein distance or root mean square distance) between two point clouds, or, more generally, two discrete dis…
Entropic optimal transport is maximum-likelihood deconvolution
Philippe Rigollet, Jonathan Weed
We give a statistical interpretation of entropic optimal transport by showing that performing maximum-likelihood estimation for Gaussian deconvolution corresponds to calculating a…
An explicit analysis of the entropic penalty in linear programming
Jonathan Weed
Solving linear programs by using entropic penalization has recently attracted new interest in the optimization community, since this strategy forms the basis for the fastest-known…
Uncoupled isotonic regression via minimum Wasserstein deconvolution
Philippe Rigollet, Jonathan Weed
Isotonic regression is a standard problem in shape-constrained estimation where the goal is to estimate an unknown nondecreasing regression function from independent pairs $(x_…
Statistical Optimal Transport via Factored Couplings
Aden Forrow, Jan-Christian Hütter, Mor Nitzan +3
We propose a new method to estimate Wasserstein distances and optimal transport plans between two probability distributions from samples in high dimension. Unlike plug-in rules tha…